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Bibliographic record
Abstract
The objective of this report was to analyze what influence the statutory quality control\nperformed by “Revisortilsynet" has had on the auditing business, focusing primarily on\nthe smaller auditing firms. This subject is interesting since the annual reports from the\ngoverning entity "Revisortilsynet", seems to indicate that almost a quarter of the\nauditing firms selected for statutory quality control, voluntarily deregistered from\nRevireg.\nThe report describes the legislation regarding statutory quality control and describes\nthe difference in perceived burdens by smaller and larger auditing firms.\nThe analysis of the firms, who had voluntarily deregistered from Revireg, found that\nthe high number of deregistration was primarily influenced by structural causes, such\nas mergers and acquisitions, and possibly the high average age of auditors in smaller\nfirms. The impact of statutory quality control was found to be much smaller than the\ninitial indications could lead one to believe.\nThe analysis did however find that the statutory quality control was a primary reason,\nfor those that deregistered from Revireg for reason not related to structural issues.\nThe smaller auditing firms found the quality control system to be cumbersome,\nexpensive and with no real effect on the quality of the work provided.\nThe report then addressed the regulatory conditions for those firms that no longer\nregistered in Revireg. Here I found that the regulatory constraints were severe. The\n“Revisorlov” prohibited these firms from offering auditing of annual reports, to\ncompanies for whom auditing was mandatory. Even for those companies that had\nchosen not to have their annual report audited, there was found to be regulatory\nconstraints. Here in the form of “Årsregnskabsloven” that states that only government\napproved auditors is allowed to make a statement in an annual report.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.338 | 0.196 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".